You see nanomachines all the time. You just call them cpus, for example. Just because they arent flapping around doesn't mean they are not doing an important job. Health care (not my area) makes extensive use of computers.

Gate sizes are tiny - larger than advertised by cpu manufacturers, who like to redefine what their widths refer to but still incredibly dense. A finfet is about 20-30nm across the core, and is so small it is hard to get good imagery with common methods. This would not be possible without modern nanotechnology.

You are seeing the effects of polycrystalline diffraction. If you were to pass the light through a single crystal, you would see something like a spot or line pattern (kikuchi bands).

Because the orientation of the ice crystals are random in the atmosphere, you get a random orientation during the light scattering. summing up all these many spot patterns from each individual scattering at random rotations gives you a ring.

You could emulate the process with a stencil of dots at whatever pattern you like. Rotate it randomly and then draw in the dots from the stencil. If you do this enough, you will get a ring.

Technically there are many processes going on. Single scattering (which produces the dot pattrn) requires very small amounts of material. As the material (here ice) gets thicker, you will see lines forming (multiple scattering).

Anything with a negative jt coefficient will get colder when compressed, eg nitrogen and hydrogen over their relevant temperature ranges.

http://en.wikipedia.org/wiki/Joule-Thomson_coefficient

Ever use a pump to inflate a tyre? I've given myself small burns by underestimating how much heat was released by gas compression. When you release the pressure, the gas cools, like when using a spray can - it can also get very cold.

Different gasses will change temperatures at different rates when pressurised, this is given by the Joule Thompson coefficient Hydrogen is a notable one, as it has a negative coefficient (i.e. it does the opposite of most gasses) near room conditions.

there needs to be a lot more context to give you a good answer.

how much material do your have? do you mind if we destroy it as part of the measurement? how accurate (significant figures) do you want the result to be? what is the material made out of? how much money do you have to spend on this?

cheap simple solutions will work for some levels, but eg crushing may be to be done under vacuum to avoid trapped gas during the crush. you may even need to heat the sample to outgas it better before crushing. assuming that it can survive heating and vacuum conditions.

you could use a sectioning method with image analysis like microtomy to get a good answer, if your sample is soft enough, and you know the density of the two phases (sponge/pore). or you can go high tech, and use ct scanning to get the same answer, provided that your sample is xray transparent enough, and fits in the scanner.

i doubt you would want to try a crush method if the sample is a pu based foam!

I'm going to go out on a limb and suggest it is not raman. raman scattering is very weak, and would work better with prepared samples.

if you encode the outgoing signal as white noise, it won't clearly correlate to reflections from the environment, as you would have to subtract the random additive noise from the emitter, which would drown out the quieter reflection.

however , if you know the sequence from the emitter in advance (say you know the random key) , then you can subtract it from your inbound signal, enhancing the signal to noise .

its a bit like radar jamming, or selective availability in gps.